PPO-HRAP：结合混合制度感知策略的近端策略优化用于风险控制交易

combines Proximal Policy Optimization with an interpretable regime prior

Abstract: Reinforcement learning for trading often struggles to balance upside participation with drawdown control. Profit-only policies can collapse toward passive long exposure on upward-drifting assets, while aggressively risk-penalized rewards can become too defensive during volatile periods. This paper proposes PPO-HRAP, a hybrid regime-aware policy that combines Proximal Policy Optimization…